CUDA Turns 5!
This week marks the fifth anniversary of the CUDA programming model. To celebrate the occasion, we caught up with Ian Buck, inventor of CUDA and NVIDIA’s General Manager for GPU Computing. Here is a preview of the interview:

NVIDIA: Ian, how did you get hooked on computing with GPUs?

Ian: During my Ph.D. studies at Stanford, the trends in programmable graphics hardware were really exciting to me as well as the opportunity to work on technology that could influence a wide breadth of sciences, whether it was molecular dynamics, mechanical engineering or turbulence research. I could see that GPUs were becoming powerful enough to help people working on the big questions in science.

NVIDIA: How did you first start using GPUs? Was it as a programmer or a gamer?

Ian: Let’s just say that Stanford had a great internet connection, and as a result, we had an awesome QuakeServer.

NVIDIA: What’s next for GPU computing?

Ian: GPU computing is going mainstream. And it’s not just about NVIDIA. Just look at the great work being done with tools, compilers and apps. Ad hoc GPU user groups are popping up all over the world. A gigantic ecosystem is coming to life. Today, any kind of meaningful simulation is done with GPUs. This focused activity will enable us to solve some of the fundamental problems in science.

NVIDIA: What have you learned along the way, since your days at Stanford working on Brook to your current role as GM for GPU Computing?

Ian: First of all, hire great people. Don’t compromise. The people who use CUDA in industry and academia are intensely driven. I look for the same drive in the people we hire to work on CUDA at NVIDIA -- intellectual curiosity combined with a passion to solve cool and interesting problems. Second, don’t underestimate the value of working on productivity features for developers. The CUDA technology roadmap is focused on making GPU computing easier. Anything we can do to make a developer’s life easier is always worth it.

Editor’s Note: Next week, Ian will be at the SC11 conference in Seattle and would be happy to meet up with current and future CUDA users. If you can’t attend in person, be sure to check out our Facebook live stream from SC11 at: http://apps.facebook.com/nv-supercomputing/

CUDA 4.1 Release Candidate

The CUDA Toolkit v4.1 release candidate (RC1) is now available to CUDA Registered Developers. New features include an open source LLVM-based compiler, 1000+ new image processing functions and a redesigned Visual Profiler with automated performance analysis.
- See: http://developer.nvidia.com/cuda-toolkit-41-rc1

2X in 4 Weeks. Guaranteed.

Double your application performance with directives and GPUs. Simply insert a few "hints" into the compiler and it automatically optimizes and accelerates your code. To help you get started, NVIDIA and PGI are offering a free 30-day license of the directives-based PGI Accelerator compiler. Not only that, we are guaranteeing your application will achieve at least a 2X speedup in 4 weeks or less.
- See: www.nvidia.com/2xin4weeks

Leading Apps Add Multiple GPU Acceleration Support

Four top applications for materials science and biomolecular modeling - LAMMPS, GROMACS, GAMESS and QMCPACK - have added support for multiple GPU acceleration, enabling a reduction in simulation times from days to hours.
- See: http://bit.ly/uqOmu2

New CULA Sparse from EM Photonics

EM Photonics released the general availability version of CULA Sparse, a collection of matrix solvers for sparse systems on NVIDIA GPUs. In addition, new functionality has been added to CULA R13.
- See: www.culatools.com

MSC Software Announces MSC Nastran 2012

Chinese Researchers Simulate H1N1 Virus

Chinese researchers achieved a breakthrough by creating the world’s first computer simulation of a whole H1N1 influenza virus at the atomic level. Researchers at the Institute of Process Engineering of Chinese Academy of Sciences (CAS-IPE) are using molecular-dynamics simulations as a "computational microscope" to peer into the structure of the virus. The work is performed on a supercomputer with 2000+ Tesla GPUs.
- See: http://www.nvidia.com/object/newsroom.html

GPU@BU Workshop

Boston University held a research symposium and tutorial this week on GPUs in scientific computing. The event was organized by Lorena Barba, Richard Brower, Martin Herbordt and Claudio Rebbi.
- See: http://blogs.bu.edu/gpu/gpubu-workshop/